Lukas Kathrein, A. Lüder, Kristof Meixner, D. Winkler, S. Biffl
{"title":"多学科系统工程过程的生产感知分析","authors":"Lukas Kathrein, A. Lüder, Kristof Meixner, D. Winkler, S. Biffl","doi":"10.5220/0007618000480060","DOIUrl":null,"url":null,"abstract":"The Industry 4.0 vision of flexible manufacturing systems depends on the collaboration of domain experts coming from a variety of engineering disciplines and on the explicit representation of knowledge on relationships between products and production systems (PPR knowledge). However, in multi-disciplinary systems engineering organizations, process analysis and improvement has traditionally focused on one specific discipline rather than on the collaboration of several workgroups and their exchange of knowledge on product/ion, i.e., product and production processes. In this paper, we investigate requirements for the product/ion-aware analysis of engineering processes to improve the engineering process across workgroups. We introduce a product/ion-aware engineering processes analysis (PPR EPA) method, to identify gaps in PPR knowledge needed and provided. For representing PPR knowledge, we introduce a product/ion-aware data processing map (PPR DPM) by extending the BPMN 2.0 standard, adding PPR knowledge classification. We evaluate the contribution in a case study at a large production systems engineering company. The domain experts found the PPR EPA method using the PPR DPM usable and useful to trace design decisions in the engineering process as foundation for advanced quality assurance analyses.","PeriodicalId":271024,"journal":{"name":"International Conference on Enterprise Information Systems","volume":"132 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Production-Aware Analysis of Multi-disciplinary Systems Engineering Processes\",\"authors\":\"Lukas Kathrein, A. Lüder, Kristof Meixner, D. Winkler, S. Biffl\",\"doi\":\"10.5220/0007618000480060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Industry 4.0 vision of flexible manufacturing systems depends on the collaboration of domain experts coming from a variety of engineering disciplines and on the explicit representation of knowledge on relationships between products and production systems (PPR knowledge). However, in multi-disciplinary systems engineering organizations, process analysis and improvement has traditionally focused on one specific discipline rather than on the collaboration of several workgroups and their exchange of knowledge on product/ion, i.e., product and production processes. In this paper, we investigate requirements for the product/ion-aware analysis of engineering processes to improve the engineering process across workgroups. We introduce a product/ion-aware engineering processes analysis (PPR EPA) method, to identify gaps in PPR knowledge needed and provided. For representing PPR knowledge, we introduce a product/ion-aware data processing map (PPR DPM) by extending the BPMN 2.0 standard, adding PPR knowledge classification. We evaluate the contribution in a case study at a large production systems engineering company. The domain experts found the PPR EPA method using the PPR DPM usable and useful to trace design decisions in the engineering process as foundation for advanced quality assurance analyses.\",\"PeriodicalId\":271024,\"journal\":{\"name\":\"International Conference on Enterprise Information Systems\",\"volume\":\"132 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Enterprise Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0007618000480060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Enterprise Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0007618000480060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Production-Aware Analysis of Multi-disciplinary Systems Engineering Processes
The Industry 4.0 vision of flexible manufacturing systems depends on the collaboration of domain experts coming from a variety of engineering disciplines and on the explicit representation of knowledge on relationships between products and production systems (PPR knowledge). However, in multi-disciplinary systems engineering organizations, process analysis and improvement has traditionally focused on one specific discipline rather than on the collaboration of several workgroups and their exchange of knowledge on product/ion, i.e., product and production processes. In this paper, we investigate requirements for the product/ion-aware analysis of engineering processes to improve the engineering process across workgroups. We introduce a product/ion-aware engineering processes analysis (PPR EPA) method, to identify gaps in PPR knowledge needed and provided. For representing PPR knowledge, we introduce a product/ion-aware data processing map (PPR DPM) by extending the BPMN 2.0 standard, adding PPR knowledge classification. We evaluate the contribution in a case study at a large production systems engineering company. The domain experts found the PPR EPA method using the PPR DPM usable and useful to trace design decisions in the engineering process as foundation for advanced quality assurance analyses.